---
title: "COVID-19"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    social: menu
    source_code: embed
    vertical_layout: fill
---

```{r setup, include=FALSE}
#---------------------- Update Data ------
library(flexdashboard)
#devtools::install_github("RamiKrispin/coronavirus")
library(coronavirus)

data("coronavirus")

#------------------ Parameters ------------------
# Set colors
# https://www.w3.org/TR/css-color-3/#svg-color
confirmed_color <- "purple"
active_color <- "#1f77b4"
recovered_color <- "forestgreen"
death_color <- "red"
varios <- c("Brazil", "Argentina", "Italy", "US", "Germany", "Spain", "Chile", "Japan")
country <- c("Brazil")
```


```{r df_totals, include=FALSE}
#------------- Data - Total cases in the country --------------
`%>%` <- magrittr::`%>%`
df_totals <- coronavirus %>% 
  dplyr::filter(Country.Region %in% country) %>% 
  dplyr::group_by(Country.Region, type) %>% 
  dplyr::summarise(total = sum(cases)) %>% 
  tidyr::pivot_wider(names_from = type, 
                     values_from = total) %>% 
  dplyr::arrange(-confirmed) %>% 
  dplyr::ungroup() %>% 
  dplyr::mutate(country = Country.Region) %>% 
  dplyr::mutate(country = trimws(country)) %>% 
  dplyr::mutate(country = factor(country, levels = country))
```

```{r df_daily, include=FALSE}
#------------- Data - Total cases daily --------------
`%>%` <- magrittr::`%>%`
df_daily <- coronavirus %>% 
  dplyr::filter(Country.Region %in% c("Brazil")) %>% 
  dplyr::group_by(date, type) %>% 
  dplyr::summarise(total = sum(cases, na.rm = TRUE)) %>% 
  tidyr::pivot_wider(names_from = type, 
                     values_from = total) %>% 
  dplyr::arrange(date) %>% 
  dplyr::ungroup() %>% 
  dplyr::mutate(active = confirmed - death - recovered) %>% 
  dplyr::mutate(
    confirmed_cum = cumsum(confirmed),
    death_cum = cumsum(death),
    recovered_cum = cumsum(recovered),
    active_cum = cumsum(active)
  )
```


Brasil
=======================================================================
Row
-----------------------------------------------------------------------
### confirmed {.value-box}
```{r}
valueBox(value = df_totals$confirmed, 
         caption = "Casos confirmados", 
         icon = "fas fa-user-md", 
         color = confirmed_color)
```

### active {.value-box}
```{r}
valueBox(value = (df_totals$confirmed - df_totals$death - df_totals$recovered), 
         caption = "Ativos", 
         icon = "fas fa-user-md", 
         color = active_color)
```

### death {.value-box}
```{r}
valueBox(value = df_totals$death, 
         caption = "Mortes confirmadas", 
         icon = "fas fa-user-md", 
         color = death_color)
```

### recovery {.value-box}
```{r}
valueBox(value = df_totals$recovered, 
         caption = "Recuperados", 
         icon = "fas fa-user-md", 
         color = recovered_color)
```

Row
-----------------------------------------------------------------------

### **Casos acumulados diariamente** (Brasil)
```{r}
plotly::plot_ly(data = df_daily) %>%
  plotly::add_trace(
    x = ~date,
    y = ~confirmed_cum,
    type = "scatter",
    mode = "lines+markers",
    # name = "Active",
    name = "Confirmados",
    line = list(color = confirmed_color),
    marker = list(color = confirmed_color)
  ) %>%
plotly::add_trace(
    x = ~date,
    y = ~death_cum,
    type = "scatter",
    mode = "lines+markers",
    name = "Mortes",
    line = list(color = death_color),
    marker = list(color = death_color)
  ) %>%
plotly::add_trace(
    x = ~date,
    y = ~recovered_cum,
    type = "scatter",
    mode = "lines+markers",
    name = "Recuperados",
    line = list(color = recovered_color),
    marker = list(color = recovered_color)
  ) %>%
  plotly::add_trace(
    x = ~date,
    y = ~active_cum,
    type = "scatter",
    mode = "lines+markers",
    name = "Ativos",
    line = list(color = active_color),
    marker = list(color = active_color)
  ) %>% 
  plotly::add_annotations(
    x = as.Date("2020-02-26"),
    y = 1,
    text = paste("Primeiro Caso"),
    xref = "x",
    yref = "y",
    arrowhead = 5,
    arrowhead = 3,
    arrowsize = 1,
    showarrow = TRUE,
    ax = -10,
    ay = -40
  ) %>%
  plotly::add_annotations(
    x = as.Date("2020-03-05"),
    y = 3,
    text = paste("Primeira Transmissão Interna"),
    xref = "x",
    yref = "y",
    arrowhead = 5,
    arrowhead = 3,
    arrowsize = 1,
    showarrow = TRUE,
    ax = -90,
    ay = -90
  ) %>%
  plotly::add_annotations(
    x = as.Date("2020-03-17"),
    y = 3,
    text = paste("Primeira Morte"),
    xref = "x",
    yref = "y",
    arrowhead = 5,
    arrowhead = 3,
    arrowsize = 1,
    showarrow = TRUE,
    ax = -90,
    ay = -60
  ) %>%
  plotly::layout(
    title = "",
    yaxis = list(title = "Número de casos acumulados"),
    xaxis = list(title = "Data"),
    legend = list(x = 0.1, y = 0.9),
    hovermode = "compare"
  )
```

Row
-----------------------------------------------------------------------

### **Ocorrências por dia** (novos / recuperados / mortes no dia)

```{r daily_summary}
plotly::plot_ly(data = df_daily, 
                x = ~ df_daily$date, 
                y = ~ df_daily$active, 
                type = "bar", 
                name = "Ativos",
                marker = list(color = active_color)) %>%
  plotly::add_trace(y = ~ df_daily$recovered, 
                    # text =  ~ recovered, 
                    # textposition = 'auto',
                    name = "Recuperados",
                    marker = list(color = recovered_color)) %>%
  plotly::add_trace(y = ~ df_daily$death, 
                    # text =  ~ death, 
                    # textposition = 'auto',
                    name = "Mortes",
                    marker = list(color = death_color)) %>%
  plotly::layout(barmode = 'stack',
                 yaxis = list(title = "Eventos no dia\n (escala Logarítmica)",
                              type = "log"),
                 xaxis = list(title = ""),
                 hovermode = "compare",
                  margin =  list(
                   # l = 60,
                   # r = 40,
                   b = 10,
                   t = 10,
                   pad = 2
                 ))
```



Mundo
=======================================================================


```{r wd_totals, include=FALSE}
#------------- Data - Total cases by country --------------
`%>%` <- magrittr::`%>%`
wd_totals <- coronavirus %>% 
  dplyr::filter(Country.Region %in% varios) %>% 
  dplyr::group_by(Country.Region, type) %>% 
  dplyr::summarise(total = sum(cases)) %>% 
  tidyr::pivot_wider(names_from = type, 
                     values_from = total) %>% 
  dplyr::arrange(-confirmed) %>% 
  dplyr::ungroup() %>% 
  dplyr::mutate(country = Country.Region) %>% 
  dplyr::mutate(country = trimws(country)) %>% 
  dplyr::mutate(country = factor(country, levels = country))
```


Row
-----------------------------------------------------------------------
### confirmed {.value-box}
```{r}
valueBox(value = sum(wd_totals$confirmed), 
         caption = "Casos confirmados (nos países abaixo)", 
         icon = "fas fa-user-md", 
         color = "purple")
```


### active {.value-box}
```{r}
valueBox(value = ((sum(wd_totals$confirmed) - sum(wd_totals$death) - sum(wd_totals$recovered))),
         caption = "Ativos", 
         icon = "fas fa-user-md", 
         color = active_color)
```


### death {.value-box}
```{r}
valueBox(value = sum(wd_totals$death), 
         caption = "Mortes confirmadas (nos países abaixo)", 
         icon = "fas fa-user-md", 
         color = "red")
```

### recovered {.value-box}
```{r}
valueBox(value = sum(wd_totals$recovered), 
         caption = "Recuperados (nos países abaixo)", 
         icon = "fas fa-user-md", 
         color = "green")
```

Row
-----------------------------------------------------------------------


```{r wd_daily, include=FALSE}
#------------- Data - Total cases daily --------------
`%>%` <- magrittr::`%>%`
wd_daily <- coronavirus %>% 
  dplyr::filter(Country.Region %in% varios) %>% 
  dplyr::group_by(date, Country.Region, type) %>% 
  dplyr::summarise(total = sum(cases, na.rm = TRUE)) %>% 
  dplyr::filter(type == "confirmed") %>% 
  tidyr::pivot_wider(names_from = Country.Region, 
                     values_from = total, values_fill = list(total = 0)) %>% 
  dplyr::arrange(date)
  

```


### **Casos acumulados por tipo**
```{r}

plotly::plot_ly(data = wd_daily) %>% 
  plotly::add_trace(
    x = ~date,
    y = ~Argentina,
    type = "scatter",
    mode = "lines+markers",
    name = "Argentina"
  ) %>%
  plotly::add_trace(
    x = ~date,
    y = ~Brazil,
    type = "scatter",
    mode = "lines+markers",
    name = "Brazil"
  ) %>% 
  plotly::add_trace(
    x = ~date,
    y = ~US,
    type = "scatter",
    mode = "lines+markers",
    name = "US"
  ) %>% 
  plotly::add_trace(
    x = ~date,
    y = ~Germany,
    type = "scatter",
    mode = "lines+markers",
    name = "Germany"
  ) %>% 
  plotly::add_trace(
    x = ~date,
    y = ~Japan,
    type = "scatter",
    mode = "lines+markers",
    name = "Japan"
  ) %>% 
  plotly::add_trace(
    x = ~date,
    y = ~Chile,
    type = "scatter",
    mode = "lines+markers",
    name = "Chile"
  ) %>% 
  plotly::layout(yaxis = list(title = "Eventos no dia\n (escala Logarítmica)",
                              type = "log"),
                 xaxis = list(title = ""),
                 hovermode = "compare",
                  margin =  list(
                   # l = 60,
                   # r = 40,
                   b = 10,
                   t = 10,
                   pad = 2
                 ))


```